Data science case studies and machine learning models on various publicly available datasets
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Updated
Apr 28, 2019 - Python
Data science case studies and machine learning models on various publicly available datasets
To predict the price of the Google stock, we use Deep Learning, Recurrent Neural Networks with Long Short-Term Memory(LSTM) layers.
RNN model for prediction of bitcoin prices
Neural Network based on the Seq2Seq from Code5T to analyze code and give you a summary in plain English(natural language). This is a POC for codesapiens.ai
The task of post modifier generation requires to automatically generate a post modifier phrase describing the target entity (an entity essentially refers to a noun but here we only consider people) that contextually fits in the input sentence.
Sentiment analysis and prediction project based on a Recurrent Neural Network Model (RNN) that can read in some text and make a prediction about the sentiment of that text.
Recurrent Neural Network that takes prime character and generate character from it.
Word RNN generating text
Stock Prediction Web Application using flask.
En utilisant, un RNN (réseau de neurones récurrents), je vais générer de la musique du style du groupe ‘The Chainsmokers’ c’est-à-dire de la musique POP.
IceCube - Neutrinos in Deep Ice
Rule based chat-bot using CNN based on multi class text classification which responds to all queries on Deep Learning class. As a fallback option added generative chat-bot trained on cornell movie dialog corpus using sequence to sequence RNN model.
Contains assignments I did in ML course
Given 10 predefined relations like cause-effect, product-producer, etc, the goal was to define the relation and the direction of the relation b/w 2 entities in a sentence.
A completely voice based sophisticated AI system that does almost exactly what a normal assistant does for you only with better efficiency. Everything and every code used in this project is totally hard-coded by me.
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